Development of a Mobile App for Remote Post-Stroke Rehabilitation Engagement

Thesis Abstract

Post-stroke rehabilitation is a critical component of recovery, yet adherence to prescribed therapy regimens remains a significant challenge, often resulting in suboptimal functional outcomes. This study addresses the increasing need for innovative solutions to enhance patient engagement and compliance in rehabilitation programs by developing a mobile application designed specifically for remote post-stroke rehabilitation engagement. The primary aim is to create and evaluate a user-centered, evidence-based mobile app that facilitates accessible, interactive, and personalized rehabilitation exercises, thereby improving adherence and clinical outcomes among stroke survivors. The specific objectives include (1) to identify the key behavioral and clinical factors influencing rehabilitation adherence in stroke patients; (2) to design a mobile application incorporating features aligned with behavioral change theories, such as the Health Belief Model and the Self-Determination Theory; (3) to assess the usability, acceptability, and engagement levels of the developed app through qualitative and quantitative methods; and (4) to evaluate the impact of the app on rehabilitation adherence and functional recovery through a controlled experimental study. Employing a mixed-methods research design, the study combines qualitative interviews and focus groups with stroke survivors, caregivers, and rehabilitation professionals to inform app development; followed by a quantitative randomized controlled trial (RCT). The target population comprises stroke patients within six months post-event, residing in urban healthcare facilities, with an estimated sample size of 150 participants, allocated randomly into intervention and control groups. The intervention group will use the mobile app over a 12-week period, while the control group follows standard care protocols. Data collection instruments include validated questionnaires measuring adherence (e.g., the Stroke Rehabilitation Adherence Questionnaire), usability (System Usability Scale), and functional outcomes (Modified Rankin Scale, Fugl-Meyer Assessment). Additionally, semi-structured interviews will explore user perspectives. Data analysis will involve descriptive statistics, independent t-tests, and chi-square tests for quantitative data, while regression analysis will identify predictors of adherence improvement. Thematic analysis will be applied to qualitative interview transcripts to extract insights regarding user experience and engagement barriers. To evaluate effectiveness, ANCOVA will compare post-intervention outcomes adjusting for baseline measures. Expected findings include significant improvements in rehabilitation adherence rates among app users, enhanced functional recovery scores, and high usability and acceptability ratings. The app’s features, grounded in behavioral theories, are anticipated to foster motivation, self-efficacy, and sustained engagement. The study aims to contribute to knowledge by empirically evidencing the efficacy of ICT-driven interventions in supporting post-stroke rehabilitation, particularly in remote and home-based settings. The main conclusion underscores the potential of mobile health applications to transform conventional rehabilitation practices by making them more accessible, personalized, and engaging. The study advocates for integrating such technological solutions into routine clinical care and suggests policy frameworks to support their implementation. Recommendations include further research on long-term adherence, customization for diverse populations, and integration with tele-rehabilitation platforms to maximize scalability and impact. This research ultimately advances the approach to post-stroke care through innovative, technology-enabled strategies rooted in behavioral science, thus contributing to both clinical practice and health technology development.